Triple

T7862632
Position Surface form Disambiguated ID Type / Status
Subject Mark Fiennes E182535 entity
Predicate notableRelative P367 FINISHED
Object Magnus Fiennes E178452 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Magnus Fiennes | Statement: [Mark Fiennes, notableRelative, Magnus Fiennes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Magnus Fiennes
Context triple: [Mark Fiennes, notableRelative, Magnus Fiennes]
  • A. Magnus Fiennes chosen
    Magnus Fiennes is a British composer, record producer, and songwriter known for his work in film, television, and pop music.
  • B. Mark Fiennes
    Mark Fiennes was an English photographer and illustrator, best known as the father of actors Ralph and Joseph Fiennes.
  • C. Joseph Fiennes
    Joseph Fiennes is an English actor known for his roles in films such as "Shakespeare in Love" and various historical and dramatic productions in both cinema and television.
  • D. William Fiennes
    William Fiennes is an English writer and memoirist best known for his acclaimed books "The Snow Geese" and "The Music Room."
  • E. Ralph Fiennes
    Ralph Fiennes is an acclaimed English actor and filmmaker known for his intense, nuanced performances in films such as Schindler's List, the Harry Potter series, and The Grand Budapest Hotel.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb36be5f408190b82a097b0825c57a completed March 31, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde6a2bdd08190897705615109dae0 completed April 2, 2026, 3:46 a.m.
Created at: March 30, 2026, 4:53 p.m.